{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def funy(x):\n",
    "    if(abs(x) <= 1):\n",
    "        y = 2-x**2\n",
    "    elif(abs(x)<= 2):\n",
    "        y = (abs(x)-2)**2\n",
    "    else:\n",
    "        y = 0\n",
    "    return y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xNm0abN0KffuGTiKSHvXq+ZEwrSuQDFApkHibMgWOPRYaNw6dRCR9Tj/dj4h9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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b411717940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = np.linspace(-3,3,2000)\n",
    "Y = [funy(x) for x in X ]\n",
    "plt.plot(X,Y,'r')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
